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Carlos Henrique da Silva Santos, Kleucio Claudio, Marcos Sergio Goncalves, Juliano Rodrigues Brianeze and Hugo Enrique Hernandez-Figueroa
This work presents the efficiency and the stochastic nature of three bio-inspired algorithms combining four different probability density functions (PDF) to design Microstrip Antennas (MSAs). The project of MSAs considers single and multi-objective versions. The algorithms examined are Genetic Algorithm (GA), Evolution Strategies (ES) and Artificial Immune Systems (AIS). In these algorithms, bandwidth (BW), standing wave rate (SWR) and radiation efficiency (RE) are parameters to be optimized. The results show interesting computational performance of the algorithms in single and multi-objective applications, combining different PDFs and bio-inspired algorithms. Other interesting result is presented when there is absence of memory resource. These results emphasize the efficiency of the algorithms to optimize MSAs and the possibility to apply in others electromagnetic problems.
Microstrip Antenna Design, Computational Electromagnetism, Bio-Inspired Algorithms, Multi-objective Optimization.
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